This is a generated RPPA Report generated from the following scripts,
-Pathway_Score_calculator.ipynb - Score_Caluclator.Rmd (eventually this will be encorporated into the Pathway_Score_calculator.ipynb) -Pathway_Score_calculator.ipynb -Pathway_prepare_Density_maper.Rmd -Heat_mapper.Rmd -RPPA_Report.Rmd
All Scripts must be run prior to running this script or it will not work,Knit this file together and a HTML report will be generated if you wish to change the format of this file you may alter HTML instructions.
packages and data read in
First Lets take a look at the pathway Scores
Lets look at the pathway scoring
kbl(Pathway_key, booktabs = T)| Pathway | Predictor | Weight | Count | |
|---|---|---|---|---|
| 2 | Apoptosis | CASPASE7CLEAVEDD198 | 1 | 1 |
| 3 | Apoptosis | Caspase-8 | 1 | 1 |
| 4 | Apoptosis | Caspase_3_cleaved | 1 | 1 |
| 5 | BH3_Balance | BAK | 1 | 1 |
| 6 | BH3_Balance | BAX | 1 | 1 |
| 7 | BH3_Balance | BID | 1 | 1 |
| 8 | BH3_Balance | BIM | 1 | 1 |
| 9 | BH3_Balance | MCL-1 | -1 | 1 |
| 10 | BH3_Balance | BADPS112 | -1 | 1 |
| 11 | BH3_Balance | BCL2 | -1 | 1 |
| 12 | BH3_Balance | BCLXL | -1 | 1 |
| 13 | BH3_Balance | CIAP2 | -1 | 1 |
| 14 | Cell_cycle_progression | Cyclin-B1 | 1 | 1 |
| 15 | Cell_cycle_progression | PLK1 | 1 | 1 |
| 16 | Cell_cycle_progression | CDK1_pT14 | 1 | 1 |
| 17 | Cell_cycle_progression | Chk1 | 1 | 1 |
| 18 | Cell_cycle_progression | cdc25C | 1 | 1 |
| 19 | Cell_cycle_progression | Rb_pS807_S811 | 1 | 1 |
| 20 | Cell_cycle_progression | p21 | -1 | 1 |
| 21 | Cell_cycle_progression | p27_pT198 | -1 | 1 |
| 22 | Cell_cycle_progression | CyclinD1 | -1 | 1 |
| 23 | Cell_cycle_progression | 1433BETA | -1 | 1 |
| 24 | DNA_Damage | Histone-H3 | 1 | 1 |
| 25 | DNA_Damage | H2AX_pS139 | 1 | 1 |
| 26 | DNA_Damage | H2AX_pS140 | 1 | 1 |
| 27 | DNA_Damage_Checkpoint | ATM_pS1981 | 1 | 1 |
| 28 | DNA_Damage_Checkpoint | ATR_pS428 | 1 | 1 |
| 29 | DNA_Damage_Checkpoint | CDK1_pY15 | 1 | 1 |
| 30 | DNA_Damage_Checkpoint | Chk1_pS296 | 1 | 1 |
| 31 | DNA_Damage_Checkpoint | Chk2_pT68 | 1 | 1 |
| 32 | DNA_Damage_Checkpoint | Wee1_pS642 | 1 | 1 |
| 33 | G0_G1 | 1433BETA | 1 | 1 |
| 34 | G0_G1 | 53BP1 | 1 | 1 |
| 35 | G0_G1 | BRD4 | -1 | 1 |
| 36 | G0_G1 | Cyclin-D1 | 1 | 1 |
| 37 | G0_G1 | Cyclin-B1 | -1 | 1 |
| 38 | G0_G1 | p27_pT198 | 1 | 1 |
| 39 | G0_G1 | p21 | 1 | 1 |
| 40 | G1_S | 53BP1 | 1 | 1 |
| 41 | G1_S | BRD4 | 1 | 1 |
| 42 | G1_S | Cyclin-E1 | 1 | 1 |
| 43 | G2_M | Cyclin-B1 | 1 | 1 |
| 44 | G2_M | PLK1 | 1 | 1 |
| 45 | G2_M | CDK1_pT14 | 1 | 1 |
| 46 | G2_M | cdc25C | 1 | 1 |
| 47 | G2_M | Rb_pS807_S811 | 1 | 1 |
| 48 | Hormone_receptor | ERALPHA | 1 | 1 |
| 49 | Hormone_receptor | PR | 1 | 1 |
| 50 | Hormone_receptor | AR | 1 | 1 |
| 51 | Hormone_signaling_Breast | GATA3 | 1 | 1 |
| 52 | Hormone_signaling_Breast | BCL2 | 1 | 1 |
| 53 | Hormone_signaling_Breast | ERALPHA_pS118 | 1 | 1 |
| 54 | Immune | Lck | 1 | 1 |
| 55 | Immune | ZAP-70 | 1 | 1 |
| 56 | Immune | CD4 | 1 | 1 |
| 57 | Immune | CD45 | 1 | 1 |
| 58 | Immune_Checkpoint | B7-H4 | 1 | 1 |
| 59 | Immune_Checkpoint | PD-L1 | 1 | 1 |
| 60 | Immune_Checkpoint | PD-1 | 1 | 1 |
| 61 | Immune_Checkpoint | B7-H3 | 1 | 1 |
| 62 | Notch | Jagged1 | 1 | 1 |
| 63 | Notch | Notch3 | 1 | 1 |
| 64 | Notch | TAZ | 1 | 1 |
| 65 | Notch | YAP | 1 | 1 |
| 66 | Notch | YAP_pS127 | -1 | 1 |
| 67 | PI3K_Akt | Akt_pS473 | 0.5 | 0.5 |
| 68 | PI3K_Akt | Akt_pT308 | 0.5 | 0.5 |
| 69 | PI3K_Akt | GSK3ALPHABETA_pS21S9 | 1 | 1 |
| 70 | PI3K_Akt | p27_pT198 | 1 | 1 |
| 71 | PI3K_Akt | PRAS40_pT246 | 1 | 1 |
| 72 | PI3K_Akt | PTEN | -1 | 1 |
| 73 | RAS_MAPK | B-Raf_pS445 | 1 | 1 |
| 74 | RAS_MAPK | c-Jun_pS73 | 1 | 1 |
| 75 | RAS_MAPK | C-Raf_pS338 | 1 | 1 |
| 76 | RAS_MAPK | MEK1_p_S217-S221 | 1 | 1 |
| 77 | RAS_MAPK | P38_pT180Y182 | 1 | 1 |
| 78 | RAS_MAPK | p90RSK_pT573 | 1 | 1 |
| 79 | RAS_MAPK | YB1_pS102 | 1 | 1 |
| 80 | RAS_MAPK | MAPK_pT202Y204 | 1 | 1 |
| 81 | RTK | CMET_pY1235 | 1 | 1 |
| 82 | RTK | EGFR_pY1173 | 1 | 1 |
| 83 | RTK | HER2_pY1248 | 1 | 1 |
| 84 | RTK | HER3_pY1289 | 1 | 1 |
| 85 | RTK | IGF1R_pY1135_Y1136 | 1 | 1 |
| 86 | RTK | IRS1 | 1 | 1 |
| 87 | RTK | Src_pY527 | 1 | 1 |
| 88 | RTK | SHP-2_pY542 | 1 | 1 |
| 89 | RTK | Shc_pY317 | 1 | 1 |
| 90 | RTK | Src_pY416 | 1 | 1 |
| 91 | TSC_mTOR | 4E-BP1_pS65 | 1 | 1 |
| 92 | TSC_mTOR | mTOR_pS2448 | 1 | 1 |
| 93 | TSC_mTOR | p70-S6K_pT389 | 1 | 1 |
| 94 | TSC_mTOR | Rb_pS807_S811 | 1 | 1 |
| 95 | TSC_mTOR | Rictor_pT1135 | 1 | 1 |
| 96 | TSC_mTOR | S6_pS235_S236 | 0.5 | 0.5 |
| 97 | TSC_mTOR | S6_pS240_S244 | 0.5 | 0.5 |
| 98 | Tumor_Content | BETACATENIN | 1 | 1 |
| 99 | Tumor_Content | Claudin-7 | 1 | 1 |
| 100 | Tumor_Content | E-Cadherin | 1 | 1 |
| 101 | Tumor_Content | RBM15 | 1 | 1 |
| 102 | Tumor_Content | EPPK1 | 1 | 1 |
| 103 | Tumor_Content | Caveolin-1 | -1 | 1 |
| 104 | Tumor_Content | Collagen-VI | -1 | 1 |
| 105 | Tumor_Content | Lck | -1 | 1 |
| 106 | Tumor_Content | MMP2 | -1 | 1 |
| 107 | Tumor_Content | PAI-1 | -1 | 1 |
| 108 | Histone_Alteration | DM_Histone_H3 | 1 | 1 |
| 109 | Histone_Alteration | DM_K9_Histone_H3 | 1 | 1 |
| 110 | Histone_Alteration | U_Histone_H2B | 1 | 1 |
| 111 | RPA32_pS4_S8 | RPA32_pS4_S8 | 1 | 1 |
| 112 | RRM1 | RRM1 | 1 | 1 |
| 113 | RRM2 | RRM2 | 1 | 1 |
| 114 | JAK-STAT | STAT3_pY705 | 1 | 1 |
| 115 | JAK-STAT | STAT5ALPHA | 1 | 1 |
| 116 | JAK-STAT | JAK2 | 1 | 1 |
| 117 | Epigenetic | DNMT1 | 1 | 1 |
| 118 | Epigenetic | ARID1A | 1 | 1 |
| 119 | Epigenetic | BRD4 | 1 | 1 |
Now lets look at the the proteins that were dropped from the Pathways analysis
The following samples are missing
#Our Sample Patient ______ is missing
#This part will need to be altered depending on our patient of intrest
Missing_Sample_for_Our_patient<-Missing_Samples%>%filter(Sample=="261035")
reactable(Missing_Sample_for_Our_patient)Sepcifically it is missing the following proteins
Missing_Proteins_Full<-Missing_Proteins_Full%>%select(Predictor,"261035")#THIS NEEDS TO BE ALTERED TO DISIRED SAMPLE OR SAMPLES
proteins<-Missing_Proteins_Full[is.na(Missing_Proteins_Full$`261035`),]
reactable(proteins)The Following Proteins are missing
We can also visualize the missing proteins in histograms to make it more understandable #There was ____ Samples with a largen than normal missing amount of proteins these were removed and the graph was remade for visability purposes
#This section is going to have to be used on a case by case basis bedpending on how many missing samples are present
Missing_Proteins2<-Missing_Proteins%>%filter(Protein != "CASPASE3CLEAVED")
col2<-ggplot(Missing_Proteins2, aes(Protein,Amount_Missing,fill=Protein))+geom_col()+theme_classic()+ ggtitle("Missing Proteins By Amount Missing")+ theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))+ theme(legend.position="none")
col2